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CIS
2005
Springer
14 years 1 months ago
An Improved EMASK Algorithm for Privacy-Preserving Frequent Pattern Mining
Abstract. As a novel research direction, privacy-preserving data mining (PPDM) has received a great deal of attentions from more and more researchers, and a large number of PPDM al...
Congfu Xu, Jinlong Wang, Hongwei Dan, Yunhe Pan
PODS
2003
ACM
151views Database» more  PODS 2003»
14 years 7 months ago
Feasible itemset distributions in data mining: theory and application
Computing frequent itemsets and maximally frequent itemsets in a database are classic problems in data mining. The resource requirements of all extant algorithms for both problems...
Ganesh Ramesh, William Maniatty, Mohammed Javeed Z...
CIKM
2009
Springer
14 years 11 days ago
A novel approach for privacy mining of generic basic association rules
Data mining can extract important knowledge from large data collections - but sometimes these collections are split among various parties. Privacy concerns may prevent the parties...
Moez Waddey, Pascal Poncelet, Sadok Ben Yahia
SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
14 years 1 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
SAC
2006
ACM
14 years 1 months ago
A probability analysis for candidate-based frequent itemset algorithms
This paper explores the generation of candidates, which is an important step in frequent itemset mining algorithms, from a theoretical point of view. Important notions in our prob...
Nele Dexters, Paul W. Purdom, Dirk Van Gucht